görüntü-işleme

Learn what image features are, why they are important, and why corners are good features. Covers the basics of feature detection and description.

Learn to use marker-based image segmentation using watershed algorithm. We cover cv.watershed() with distance transform to segment touching objects.

Learn to use GrabCut algorithm to extract foreground in images. We cover cv2.grabCut() with both rectangle and mask initialization modes.

Learn about the hierarchy of contours, i.e. the parent-child relationship in Contours. We cover RETR_LIST, RETR_EXTERNAL, RETR_CCOMP and RETR_TREE flags with examples.

Learn about convexity defects, finding shortest distance from a point to a polygon, and matching different shapes. We cover cv2.convexityDefects(), cv2.pointPolygonTest() and cv2.matchShapes().

Learn to extract frequently used properties of objects like Solidity, Equivalent Diameter, Mask image, Mean Intensity. Also covers extreme points, aspect ratio, and more.

Learn to find different features of contours like area, perimeter, centroid, bounding box. We cover cv2.moments(), cv2.contourArea(), cv2.minAreaRect() and many more functions.

Learn about histogram backprojection for image segmentation and object finding. We cover cv2.calcBackProject() with both NumPy and OpenCV implementations.

Learn to find and plot 2D histograms. We will use Hue and Saturation values for color histograms with cv2.calcHist() and np.histogram2d().